The goal of the proposed research is to extend one-mode network data analysis of friendship relations (actor-by-actor network) to two-mode (actor-by-event affiliation/bipartite) network data to model the influence of co-participation in school-based organized activities on adolescent alcohol use. The first aim is to determine the utility of a new conceptualization of affiliation-based network influence by directly modeling (using multiple Network Autocorrelation Models) the effect of two-mode/affiliation exposure on drinking behavior controlling for other competing peer influences primarily those based on close friends or peers occupying similar network position. The second aim is to determine the relative contributions of multiple forms of network effects on alcohol use, and how these network effects operate together as risk factors. The research during the R00 phase will focus on structural properties and the dynamics of two-mode network structural analysis of affiliation networks in relation to alcohol. Related to this, the third aim is to estimate the new specification of two-mode Exponential Random Graph Model (ERGM) with geometric weighting technique to test the effects of co-affiliation on adolescent alcohol use, and it will be extended to longitudinal analysis by stochastically modeling the co-evolution of one-mode and two-mode networks to examine the cross-dependencies in the evolution of friendship and affiliation networks in relation to alcohol use within an actor-based modeling framework. The fourth aim is to explore social mechanisms that drive joint dynamics of affiliation network structures conditioned on one-mode friends'networks in relation to alcohol use. Addressing these questions would help establish the PI's long-term career goal of establishing herself as a specialist in two-mode network, which is separate and distinct from the primary mentor's (Thomas Valente) main approach of analyzing one-mode networks in the study of peer influence on substance use centered on adolescent alcohol use. Research for both K99 and R00 phase use data from both the National Longitudinal Study of Adolescent Health (Add Health) and from USC-collected data. Not only does the proposed study have the potential to provide insight into how school-based alcohol prevention program based on social influence model should be implemented, the proposed approach of using two-mode network data does not require the collection of network data (sociometrics). Therefore this methodology has the potential to be applied to a wide variety of studies and used in various fields of public health that traditionally have not been able to use network methods. PUBLIC HEALTH RELEVANCE: The research plan specifically uncovers new modes f peer influence that will help understand the etiology and amelioration of adolescent alcohol (and other substance) use, it explicitly addresses the NIH mission of producing knowledge related to the "behavior of living systems and the application of that knowledge to extend healthy life and reduce the burdens of illness and disability." PUBLIC HEALTH RELEVANCE: The goal of the proposed research is develop and explore the possibilities of the transmission of substance use through group affiliations, frequently in the form of school-sponsored sports or similar activities. If affiliation exposure has anywhere near the explanatory power of traditional social influence models, the expanded opportunities for data collection and influence estimation using data that is traditionally collected but not used in this way will provide a substantial new source of insight for understanding the etiology and amelioration of adolescent alcohol (and other substance) use.